“When you’re in a market that’s not growing, and you’ve got heavy users that account for 26% of your buyers and 60% of your volume who have cut back—how likely are you to get more business form them?” pondered Bonnie Riggs, restaurant industry analyst at NPD and author of the report. “Especially when they’re saying that going out to restaurants has gotten too expensive.”

She said heavy users pushed the current downturn further. Respondents to a survey that made up part of the report blamed high prices and low at-home food costs.

“Heavy users cut back the most, it was a two-point swing, which is significant when you consider how big that group is and how much volume they account for,” said Riggs.

And it might be easier to get another visit out of light restaurant users, but loyalty programs, rewards and marketing dollars pour toward heavy users.

“I think that historically we’ve always said its easier to get an additional visit form a heavy user than from a lighter users, it costs more to increase awareness and advertise and have programs that appeal to them,” said Riggs.

Amit Jain, founder and CEO of Bridg, said the standard loyalty program needs a little rethinking.

“A good portion of the loyal customers start using this loyalty card because they were coming in anyway,” said Jain. “It might be bringing in $3 million in sales, but nothing has changed in the business, the only thing that has changed is it’s associated with the card.”

And when the industry trends toward discounting, it can actually be a net loss for imperfect loyalty programs. He also suggests focusing on lighter users and one-time users. According to data from Bridg's fast-casual clients, those one-time users account for nearly half (48%) of the average fast-casual restaurant’s 31,000 unique customers.

So how does a restaurant find these light users and convert them into regulars? Well, that’s tricky, light users generally don’t sign up for loyalty memberships, they don’t generally announce themselves as light users and months down the road, they look like a new user all over again.

Jain said Bridg can both find and deliver extremely personal one-to-one marketing: highly targeted marketing based on the company’s database of 160 million personal profiles. The database pulls information from credit cards, linking transaction data to detailed proprietary data. It’s something Papa Murphy's did and something Chipotle has recently started using in the company’s push for better marketing that isn’t a BOGO or free burrito.

Jain said there are essentially three steps to the process.

“Because the merchant doesn’t know anything about this customer, we use our database to understand who these customers are and essentially create clusters of them,” said Jain. “The second part is using the same brand’s best customer and create clusters of them, then we compare the new customer cluster to a loyal customer cluster to see which customers are likely to be very close to each other and go after them.”

And finally, Bridg tracks what made customers in the loyal cluster loyal to begin with, replicating the marketing for new users.

“It’s all predictive modeling,” said Jain. “In short, the computer figures it out.”

Treating restaurant visitors more like ecommerce customers, Jain attempts to draw those first-time users down the sales funnel. Peppering them with soft marketing asks or minor discounts to bring them in without giving much away. He said like marketing from DSW or Amazon, the data-empowered marketing has been proven to increase frequency.

“We’re able to convert about 8% to 15% of them,” said Jain. “And once that happens, about 30% to 35% of them can be actually kept returning for a third, fourth and fifth trip. “So the overall value is not that you got this 15% or so converted from the first visit to the second visit, but you’re able to take them down a funnel and turn a good percentage of them into essentially regulars—someone who has real cadence without any marketing to them.”

According to the Bridg fast-casual data, an unengaged customer has an annual value of $42.79 across 2.69 visits, but a customer marketed to on the platform brings in $115.89 per year on average across 6.84 visits. That’s far above what Jain saw as the average number of customer frequency across the fast-casual client base of 2.71 yearly visits.

This data-driven marketing can push the needle and engage customers who aren’t eager to sign up for yet another email. But the marketing must be on point as well.

When Riggs surveyed diners, they unanimously said they wanted to be treated well. But discounts need to resonate; unloading unwanted or high-margin products doesn’t work.

They said, “’Give me a discount on something I want, not something you want me to have,’ maybe 10% off a regular items,” said Riggs.

Of course, the value proposition has to make sense too.

“Because margins are squeezed, restaurant operators have increased their prices too much over the last two years they’ve been increasing them more and more,” said Riggs. “Don’t take an across-the-board price increase, look at those that have the best margins and see where you can take price based on your operating margins, but when you take an across the board price increase—I’ve seen it happen every time—the consumer will find that it’s no longer a good value. When you see 63% of people saying it’s cheaper to eat at home because of food costs, convenience kind of goes out the door.”

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